Which of the following is correct regarding statistical analyses that delete cases with missing data?

Statistical analyses that delete cases with missing data are indeed appropriate when data are missing completely at random (MCAR). This means that the probability of a data point being missing is not related to the value of the data or any other variables in the dataset. When data meets this criterion, deleting cases with missing data does not introduce bias, and the remaining dataset can be considered a random sample of the original dataset.

Using listwise deletion (case deletion) under the assumption of MCAR allows researchers to perform analyses without the potential confounding effects that could arise from imputation methods, which may introduce assumptions about the nature of the missing data. In situations where data is missing at random (MAR) or missing not at random (MNAR), case deletion may lead to biased estimates and reduced statistical power, which is why this approach should only be employed when the MCAR assumption holds true.

Understanding the implications of data missingness and the appropriate handling methods is critical in research design and analysis to ensure the integrity and validity of findings.